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Record W4288032323 · doi:10.1590/0103-8478cr20210757

The effects of different particle film applications on almond trees

2022· article· en· W4288032323 on OpenAlexaff
Fırat Ege Karaat, Hasan Denizhan

Bibliographic record

VenueCiência Rural · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant responses to elevated CO2
Canadian institutionsNutrasource
Fundersnot available
KeywordsHorticultureParticle (ecology)LimitingChlorophyllParticle sizeChemistryMaterials scienceBiology

Abstract

fetched live from OpenAlex

ABSTRACT: Particle film applications have become common in agriculture today given the understanding of the effects of limiting high temperatures and solar radiation on plant physiology. This study was conducted to compare the effects of different particle materials on some physiological and fruit quality attributes of almonds. To achieve this, two non-transparent white solid and three transparent aqueous particle film materials were applied by foliar spraying on deficit irrigated almond trees (cv. Ferragnes). Membrane injury (MI), relative water content (RWC), the SPAD chlorophyll index, leaf temperature and some macro- and micro-nutrient contents were examined in addition to fruit sizes, weights, total oils and fatty acid compositions. The applied treatments significantly influenced the evaluated parameters, which indicated reduced stress and improved fruit quality. MI was found to be from 42.8 to 73.9%, RWC varied from 76.8 to 92.9%, and the K/Na ratio ranged between 103.3 and 521.0. As a result of this study, it was concluded that the observed improvements were due to the effects of the evaluated materials and that particle film applications can be beneficial in alleviating heat, light and water stress in almond trees.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.813
Threshold uncertainty score0.352

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.196
Teacher spread0.189 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2022
Admission routes1
Has abstractyes

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